3D structural prediction with docking for five stages of lymphoma

Abstract

Lymphoma is a type of cancer that originates in resistant framework during infection in battling cells called lymphocytes. Lymphoma is mainly classified into two i.e. Hodgkin's Lymphoma and Non-Hodgkin's Lymphoma. In Non-Hodgkin's Lymphoma there are four stages. In the first stage, cancer will spread to one extra −lymphatic organ or site and in remaining stages it will spread to another part of the human body. In this work, we develop a computational tool for predicting the appropriate drug at accurate dosage for each stage of Lymphoma. We are going to apply ten to twenty Non-Hodgkin's Lymphoma drugs which are taken from drug bank. Using alignment method we are predicting the stages of lymphoma, once the sequence is aligned high matches and less number of mismatches, gap, deletion and insertion can be considered as stage 1. According to the result obtained, we consider the people affected by four stages of Lymphoma and then predict the protein structural changes in each person. Simultaneously, multiple drug interact and the result is analyzed. If the obtained result has high binding affinity in docking, then the drug is adaptable for that stage. Our optimized algorithm can perform multiple drug interaction and docking prediction in 3-D structure affinity in each person.